US2009062624A1PendingUtilityA1

Methods and systems of delivering a probability of a medical condition

Assignee: NEVILLE THOMASPriority: Apr 26, 2007Filed: Apr 25, 2008Published: Mar 5, 2009
Est. expiryApr 26, 2027(~0.7 yrs left)· nominal 20-yr term from priority
G06N 7/01G16H 50/20
41
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Claims

Abstract

Methods and systems for delivering a probability that a subject has a medical condition are disclosed herein. The methods comprise calculating the probability of a medical condition using biomarker values and the rate of change of the biomarker values over time. In most embodiments, the methods comprise relations and calculations that require computer systems to execute the methods of the invention. Systems of the invention may include computer systems, as well as medical systems, such as biomarker assays and courses of medical action.

Claims

exact text as granted — not AI-modified
1 . A method of delivering a probability that a subject has a medical condition to a user comprising:
 a) calculating a posterior probability that a subject has a medical condition, wherein said subject has a biomarker trend, wherein said trend is formed by values corresponding to a biomarker for said medical condition obtained at least two different times from said subject, by relating:
 i) a probability of observing said biomarker trend for an individual with said medical condition; 
 ii) a probability of observing said biomarker trend for an individual without said medical condition; and 
 iii) a prior probability that said subject has said medical condition; and 
   b) delivering said posterior probability to a user with an output device.   
     
     
         2 . The method of  claim 1 , wherein said probability of observing said biomarker trend for an individual with said medical condition is calculated by comparing said biomarker trend to a historical probability distribution of historical biomarker trends of a population with said medical condition. 
     
     
         3 . The method of  claim 1 , wherein said probability of observing said biomarker trend for an individual without said medical condition is calculated by comparing said biomarker trend to a historical probability distribution of historical biomarker trends of a population without said medical condition. 
     
     
         4 . A method of delivering a probability that a subject has a medical condition to a user comprising:
 a) calculating a posterior probability that a subject has a medical condition, wherein said subject has a biomarker value for said medical condition, by relating:
 i) a probability of observing said biomarker value for an individual with said medical condition; 
 ii) a probability of observing said biomarker value for an individual without said medical condition; and 
 iii) a prior probability that said subject has said medical condition; and 
   b) delivering said posterior probability to a user with an output device.   
     
     
         5 . The method of  claim 4 , wherein said probability of observing said biomarker value for an individual with said medical condition is calculated by comparing said biomarker value to a historical probability distribution of historical biomarker values of a population with said medical condition. 
     
     
         6 . The method of  claim 4 , wherein said probability of observing said biomarker value for an individual without said medical condition is calculated by comparing said biomarker value to a historical probability distribution of historical biomarker values of a population without said medical condition. 
     
     
         7 . A method of delivering a probability that a subject has a medical condition to a user comprising:
 a) calculating a posterior probability that a subject has a medical condition, wherein said subject has a first biomarker value and a second biomarker value for said medical condition, wherein said second biomarker value is obtained after said first biomarker, by relating:
 i) a probability of observing said second biomarker value for an individual with said medical condition; 
 ii) a probability of observing said second biomarker value for an individual without said medical condition; 
 iii) a probability of observing a biomarker rate of change for an individual with said medical condition, wherein said biomarker rate of change is the difference of biomarker values over time; 
 iv) a probability of observing said biomarker rate of change for an individual without said medical condition; and 
 v) a prior probability that said subject has said medical condition; and 
   b) delivering said posterior probability to a user with an output device.   
     
     
         8 . The method of  claim 7 , wherein said probability of observing said biomarker rate of change for an individual with said medical condition is calculated by comparing said biomarker rate of change to a historical probability distribution of historical biomarker trends of a population with said medical condition. 
     
     
         9 . The method of  claim 7 , wherein said probability of observing said biomarker rate of change for an individual without said medical condition is calculated by comparing said biomarker rate of change to a historical probability distribution of historical biomarker trends of a population without said medical condition. 
     
     
         10 . The method of  claim 7 , wherein said probability of observing said biomarker value for an individual with said medical condition is calculated by comparing said biomarker value to a historical probability distribution of historical biomarker values of a population with said medical condition. 
     
     
         11 . The method of  claim 7 , wherein said probability of observing said biomarker value for an individual without said medical condition is calculated by comparing said biomarker value to a historical probability distribution of historical biomarker values of a population without said medical condition. 
     
     
         12 . The method of  claim 1 ,  4  or  7 , wherein said prior probability is calculated by comparing a profile of said subject to historical probabilities of said medical condition in an individual of a population; 
     
     
         13 . The method of  claim 1 ,  4 , or  7  further comprising biomarker values from a second biomarker corresponding to said medical condition. 
     
     
         14 . The method of  claim 1 ,  4 , or  7 , wherein said medical condition is cancer. 
     
     
         15 . The method of  claim 14 , wherein said cancer is prostate cancer. 
     
     
         16 . The method of  claim 1 ,  4 , or  7 , wherein said biomarker is fPSA or PSA. 
     
     
         17 . The method of  claim 1  or  7  further comprising removing a biomarker value from said biomarker trend that has a value outside a tolerance. 
     
     
         18 . The method of  claim 17 , wherein said tolerance is determined by a historical biomarker trend representing said individual of a population with said medical condition. 
     
     
         19 . The method of  claim 17 , wherein said tolerance is determined by a historical biomarker trend representing said individual of a population without said medical condition. 
     
     
         20 . The method of  claim 17 , wherein said tolerance is set by said user. 
     
     
         21 . The method of  claim 17 , wherein said tolerance is set automatically. 
     
     
         22 . The method of  claim 1 ,  4 , or  7 , wherein said calculating a posterior probability that a subject has a medical condition comprises at least one Monte Carlo simulation. 
     
     
         23 . The method of  claim 1 ,  4 , or  7 , wherein said calculating a posterior probability that a subject has a medical condition is carried out by a computer system. 
     
     
         24 . The method of  claim 23 , wherein said computer system comprises a Monte Carlo calculation engine. 
     
     
         25 . The method of  claim 1 ,  4 , or  7 , wherein said user is selected from the group consisting of the following: said subject, a medical professional, a clinical trial monitor, and a computer system. 
     
     
         26 . A method of taking a course of medical action by a user comprising initiating a course of medical action based on a posterior probability delivered from an output device to said user from a method of  claim 1 ,  4 , or  7 . 
     
     
         27 . The method of  claim 26 , wherein said course of medical action is delivering medical treatment to said subject. 
     
     
         28 . The method of  claim 27 , wherein the medical treatment is selected from a group consisting of the following: a pharmaceutical, surgery, organ resection, and radiation therapy. 
     
     
         29 . The method of  claim 28 , wherein said pharmaceutical comprises a chemotherapeutic compound for cancer therapy. 
     
     
         30 . The method of  claim 26 , wherein the course of medical action comprises administration of medical tests. 
     
     
         31 . The method of  claim 26 , wherein the course of medical action comprises medical imaging of said subject. 
     
     
         32 . The method of  claim 26 , wherein the course of medical action comprises setting a specific time for delivering medical treatment. 
     
     
         33 . The method of  claim 26 , wherein the course of medical action comprises a biopsy. 
     
     
         34 . The method of  claim 26 , wherein the course of medical action comprises a consultation with a medical professional. 
     
     
         35 . The method of  claim 26 , wherein the course of medical action comprises repeating a method of  claim 1 ,  4 , or  7 . 
     
     
         36 . The method of  claim 1 ,  47  or  7  further comprising diagnosing the medical condition of the subject by said user with said posterior probability from said output device. 
     
     
         37 . A computer readable medium comprising computer readable instructions, wherein the computer readable instructions instruct a processor to execute step a) of the method of  claim 14 , or  7 . 
     
     
         38 . The computer readable medium of  claim 37 , wherein the instructions operate in a software runtime environment. 
     
     
         39 . A data signal that is transmitted using a network, wherein the data signal comprises said posterior probability calculated in step a) of the method of  claim 1 ,  4 , or  7 . 
     
     
         40 . The data signal of  claim 39  further comprising packetized data that is transmitted through a carrier wave across the network. 
     
     
         41 . A medical information system for delivering a probability of a medical condition of a subject to a user comprising:
 a) an input device for obtaining biomarker values corresponding to a biomarker for a medical condition at least two different times from said subject, wherein said biomarker values form a biomarker trend;   b) a processor in communication with said input device, wherein said processor uses said biomarker trend to calculate a posterior probability of said subject having said medical condition;   c) a storage unit in communication with at least one of the input device and the processor, wherein said storage unit comprises at least one database comprising said biomarker values, said posterior probability, or a prior probability of said subject having said medical condition; and   d) an output device in communication with at least one of said processor and said storage unit, wherein said output device transmits said posterior probability to a user.   
     
     
         42 . The system of  claim 41 , wherein said input device is a graphical user interface of a webpage. 
     
     
         43 . The system of  claim 41 , wherein said input device is an electronic medical record. 
     
     
         44 . The system of  claim 41 , wherein said medical condition is prostate cancer. 
     
     
         45 . The system of  claim 41 , wherein said biomarker is PSA or fPSA. 
     
     
         46 . The system of  claim 41 , wherein said processor and said storage unit are part of a computer server. 
     
     
         47 . The system of  claim 41 , wherein said processor calculates a posterior probability that a subject has a medical condition by relating:
 a) a probability of observing said biomarker trend for an individual with said medical condition;   b) a probability of observing said biomarker trend for an individual without said medical condition; and   c) a prior probability that said subject has said medical condition.   
     
     
         48 . The system of  claim 41 , wherein said output device is selected from a group consisting of the following: a graphical user interface of a webpage, a print-out, and an email. 
     
     
         49 . The system of  claim 41 , wherein said communication is wireless communication. 
     
     
         50 . The system of  claim 41  further comprising a medical test for testing said subject for said medical condition. 
     
     
         51 . The system of  claim 51 , wherein said medical test is a PSA assay. 
     
     
         52 . The system of  claim 41  further comprising a medical treatment for treating said subject for said medical condition. 
     
     
         53 . The method of  claim 53 , wherein the medical treatment is selected from a group consisting of the following: a pharmaceutical, surgery, organ resection, and radiation therapy. 
     
     
         54 . A method of delivering a probability of a medical condition of a subject to a user comprising:
 a) collecting biomarker values from a subject corresponding to a biomarker for a medical condition at least two different times, wherein the biomarker values at the at least two different times form a biomarker trend;   b) exporting said biomarker trend for analysis, wherein said analysis comprises:
 calculating a posterior probability that a subject has a medical condition by relating: i) a probability of observing said biomarker trend for an individual with said medical condition; ii) a probability of observing said biomarker trend for an individual without said medical condition; and iii) a prior probability that said subject has said medical condition; 
   c) importing the results of said analysis to an output device; and   d) delivering said posterior probability to a user with said output device.

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